The AI Divide: How Global Imbalances Threaten a Truly Intelligent Future
The world’s most powerful artificial intelligence models are largely designed by Western powers, or China. This creates a significant imbalance, as these models predominantly reflect the cultures of their creators, often overlooking the nuances and needs of communities in the Global South. The limited representation of many languages – particularly those spoken in Africa – within these AI systems is a stark example of this North-South asymmetry in access to these emerging technologies.
The Rise of AI and the Growing Weight of India
Currently, countries in the North dominate the AI landscape. This year’s fourth AI summit, held in New Delhi, underscores the growing importance of India in the AI market. While India isn’t yet able to compete directly with Beijing and Washington, it’s emerging as a representative of the often-forgotten Global South in the race to develop the most powerful AI models.
The Language Barrier: A Fundamental Exclusion
Many nations are watching the AI revolution unfold without a clear path to participation. Beyond logistical challenges and resource limitations, the absence of large language models (LLMs) capable of processing certain languages mechanically excludes a vast portion of the global population. AI, including LLMs like ChatGPT, Deepseek, and Gemini, are trained on massive datasets. While multilingual, these datasets are heavily skewed towards English.
“An inclusive AI depends on the languages it speaks. Current large models massively favor English and other dominant languages,” explains Rachel Adams, founder of the Global Centre on AI Governance. LLMs rely on the knowledge they possess to respond to prompts, and languages with limited digital representation receive little acknowledgement.
The Digital Echo Chamber: Amplifying Existing Inequalities
The internet itself mirrors this asymmetry. Wikipedia serves as a prime example, with major languages boasting the most comprehensive and detailed content. This creates an “amplification effect,” where resources in dominant languages are further enriched, while less-represented languages remain marginalized. This, in turn, impacts AI training, as these systems draw heavily from readily available online content.
“African languages are practically invisible in the digital sphere. This not only reinforces existing inequalities and prejudices but also risks excluding millions of people from accessing AI-based services,” Adams emphasizes. Africa, with its thousands of languages and dialects, is frequently overlooked in the responses generated by chatbots.
A 2025 study questioned “the quality of large language models for African languages,” finding that the models studied were “all inferior to reference models optimized” for other languages and demonstrated “a significant performance gap compared to English.” This study focused on only 64 languages, while Africa is home to between 1,500 and 3,000.
Yasmine Abdillahi noted in Le Monde in January 2026 that “Africa represents nearly 20% of the world’s population, but less than 1% of the AI training data.” This disparity extends beyond language, as AI models are often designed with the cultural norms of their creators in mind, lacking a nuanced understanding of less-represented cultures.
Beyond Translation: The Importance of Cultural Context
AI can identify countries and historical events, but it struggles with a deep understanding of the cultural context within underrepresented nations. Alexis Frémeaux, innovation manager at the French Development Agency (AFD), compares it to a dubbed film – a skilled translator can convey the words, but not the implicit cultural references.
“For AI, we’ll be in exactly the same situation,” Frémeaux explains. “We’ll have AI that speaks the language, but if it only relies on American, European, or Western cultural resources, all the diversity and richness will be lost.” This can lead to users in the Global South encountering limitations and inaccuracies.
Local Initiatives: Building AI for the Future
To address this imbalance, countries in the Global South are beginning to develop local AI markets, creating tools designed by and for their communities. Chile recently launched Latam-GPT, trained with a significant proportion of Latin American data. Several African nations are also seeing the emergence of local initiatives, such as Masakhane African Languages Hub, which aims to ensure African languages and cultures are represented in the age of AI. AWA, an AI that speaks Wolof, also launched in Senegal in 2024.
Still, Seydina Ndiaye, an AI specialist in Africa, cautioned that many communities are adopting AI without government support. While there’s much talk of AI, concrete actions to advance the sector are limited.
Most current projects adapt existing AI models with local data. Frémeaux believes these initiatives, which address specific needs, are encouraging. “The more users there are, the more the content will be enriched, and the more AI can be fed with new content.”
The question of data sovereignty remains crucial for nations lacking the resources to develop their own AI systems. Without independent systems, these countries risk becoming dependent on dominant models.
FAQ: Addressing Common Concerns
- What is the biggest challenge facing AI development in the Global South? The lack of representation in training data and the dominance of English language models.
- Are there any examples of successful local AI initiatives? Yes, Chile’s Latam-GPT and projects like Masakhane African Languages Hub are promising examples.
- What can be done to address the AI divide? Investing in local data collection, developing culturally relevant AI models, and fostering collaboration between nations.
Pro Tip: Support open-source AI projects and initiatives that prioritize inclusivity and linguistic diversity.
Did you know? Africa is home to between 1,500 and 3,000 languages, yet less than 1% of AI training data represents this linguistic diversity.
What are your thoughts on the future of AI and its impact on global equity? Share your comments below!
